Filtered-s LMS algorithm for multichannel active control of nonlinear noise processes

Abstract

This correspondence proposes a novel nonlinear adaptive algorithm named as filtered-s least mean square (FSLMS) algorithm for multichannel active control of nonlinear noise processes. A reduced complexity FSLMS algorithm using filter bank approach is also suggested. The performance of the proposed algorithm is validated through computer simulations for nonlinear noise processes. It is demonstrated that the proposed method outperforms the conventional filtered-x least mean square algorithm and second-order Volterra filtered-x LMS (VFXLMS) algorithm for control of nonlinear noise processes. Computational complexity analysis shows the proposed method involves lesser number of computations as compared to second-order VFXLMS algorithm